论文部分内容阅读
水冷壁结渣是电站燃煤锅炉中的经常性故障，及时估计锅炉的结渣情况对提高锅炉运行的经济性、防止锅炉发生严重事故具有重要的意义。该文分析了可用于诊断该故障的主要特征参数，运用神经网络的方法建立了局部结渣故障诊断模型。计算结果表明，诊断迅速、结果准确。该方法简单，无需昂贵的诊断设备，有广泛的应用前景。
Slagging of water wall is a frequent failure in the coal-fired power station of the power station. It is of great significance to estimate the slagging situation of the boiler in time to improve the economy of boiler operation and prevent serious accidents in the boiler. In this paper, the main characteristic parameters that can be used to diagnose the fault are analyzed, and the local slagging fault diagnosis model is established by using neural network. The calculation results show that the diagnosis is rapid and the result is accurate. The method is simple, without expensive diagnostic equipment, has a wide range of applications.